Object recognition and tracking systems are a valuable resource for a variety of different industries. For example, recognition and/or tracking systems may be used to track groups of animals in the wild, to recognize components or sub-assemblies in a manufacturing context, to track motor vehicles, and so on. Object recognition techniques typically rely on insufficient data or unreliable analysis for recognition purposes, such as edges, blobs, centroids, cross-correlation, etc. These techniques, however, do not offer a way to reliably generate statistically significant signatures for detecting objects across a number of image frames or other visual data.